def bprop(self, grad, input, output, outGrad):
if self.dropRate > 0.0:
gpu_copy_to(grad * self.dropMask, grad)
gpu_copy_to(transpose(dot(transpose(grad), self.weight.wt)), outGrad)
self.weight.set_grad(dot(grad, transpose(input)))
add_row_sum_to_vec(self.bias.grad, grad, alpha=0.0)
def bprop(self, grad, input, output, outGrad):
if self.dropRate > 0.0:
gpu_copy_to(grad * self.dropMask, grad)
gpu_copy_to(transpose(dot(transpose(grad), self.weight.wt)), outGrad)
self.weight.set_grad(dot(grad, transpose(input)))
add_row_sum_to_vec(self.bias.grad, grad, alpha=0.0)
def bprop(self, grad, input, output, outGrad):
self.weight.grad.fill(0)
self.bias.grad.fill(0)
# bprop to next layer
cudaconv2.localImgActs(grad, self.weight.wt, outGrad, self.img_size, self.img_size,
self.outputSize, -self.padding, self.stride, self.numColor, 1, 0.0, 1.0)
# bprop weight
cudaconv2.localWeightActs(input, grad, self.weight.grad, self.img_size, self.outputSize,
self.outputSize, self.filterSize, -self.padding, self.stride, self.numColor, 1, 0.0, 1.0)
# bprop bias
add_row_sum_to_vec(self.bias.grad, grad)
def bprop(self, grad, input, output, outGrad):
self.weight.grad.fill(0)
self.bias.grad.fill(0)
# bprop to next layer
cudaconv2.localImgActs(grad, self.weight.wt, outGrad, self.img_size, self.img_size,
self.outputSize, -self.padding, self.stride, self.numColor, 1, 0.0, 1.0)
# bprop weight
cudaconv2.localWeightActs(input, grad, self.weight.grad, self.img_size, self.outputSize,
self.outputSize, self.filterSize, -self.padding, self.stride, self.numColor, 1, 0.0, 1.0)
# bprop bias
add_row_sum_to_vec(self.bias.grad, grad)
